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| דיוק מאוזן× | עֶרְכָּה (רגישות)× | |
|---|---|---|
| תחום | הערכת מודלים | הערכת מודלים |
| משפחה | MCDM | MCDM |
| שנת המקור≠ | 2010 | 20th century |
| הוגה השיטה≠ | Brodersen, Ong, Stephan, and Buhmann | Historical statistical foundations |
| סוג | Evaluation metric | Evaluation metric |
| מקור מכונן≠ | Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124. DOI ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| כינויים≠ | Average Recall, Equal-weight Average Sensitivity | Sensitivity, True Positive Rate, TPR |
| קשורות | 5 | 5 |
| תקציר≠ | Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset. | Recall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly. |
| ScholarGateמערך נתונים ↗ |
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